Multi-objective dispatching optimization of district heating systems based on thermal energy quality coefficients

Given the urgent need for renewable integration and flexible operation in energy systems, the low-carbon dispatching of district heating systems and the optimization of energy flow distribution have emerged as key research directions. Existing studies often overlook the dual attributes of thermal energy—its quantity and quality—thereby limiting the potential for comprehensive energy utilization. To address this issue, this paper proposes a multi-objective optimization framework for district heating systems that integrates exergy efficiency with economic performance. By establishing a "thermal energy quality coefficient"-based exergy evaluation model and formulating cascade thermal energy "supply-storage-utilization" balance constraints, the proposed approach optimizes the system dispatching strategies while reducing optimization complexity through convexification transformation. A case study conducted in an educational park in Tianjin, China, demonstrates that the proposed method achieves a 9.22% improvement in exergy efficiency, a 3.27% reduction in dispatching costs, and a 26.75% decrease in carbon emissions compared to conventional strategies. The combination of the Ɛ-constraint and TOPSIS decision-making methods effectively addresses the multi-objective optimization problem, thereby avoiding local optima. This work provides a novel theoretical framework for enhancing comprehensive energy utilization benefits and decarbonization in district heating systems, offering practical guidance for a sustainable energy transition.